apple9855 commited on
Commit
72a407d
1 Parent(s): 4b347ef

My first deep RL trained agent; Upload PPO LunarLander-v2 trained agent.

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 263.79 +/- 6.97
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7df72bde03a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7df72bde0430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7df72bde04c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7df72bde0550>", "_build": "<function ActorCriticPolicy._build at 0x7df72bde05e0>", "forward": "<function ActorCriticPolicy.forward at 0x7df72bde0670>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7df72bde0700>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7df72bde0790>", "_predict": "<function ActorCriticPolicy._predict at 0x7df72bde0820>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7df72bde08b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7df72bde0940>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7df72bde09d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7df72bd6ec80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1724816298649657989, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e31c2cee5f062a5f849ad4601efe6416b5e7ddedfd6b1def12e356ccc2b167aa
3
+ size 148088
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7df72bde03a0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7df72bde0430>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7df72bde04c0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7df72bde0550>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7df72bde05e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7df72bde0670>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7df72bde0700>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7df72bde0790>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7df72bde0820>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7df72bde08b0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7df72bde0940>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7df72bde09d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7df72bd6ec80>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1724816298649657989,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.015808000000000044,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 248,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 16,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null,
95
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:653c54fafba806eaed5b8f4810c6e2f8b0046beb4596a0118663f7f0fd8f3a36
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7c3903ffac5f4b508f9c8a992769e264dd593479d757df7812a20f2ca5bb2075
3
+ size 43762
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.4.0+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.26.4
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (187 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 263.7898788, "std_reward": 6.965050268889176, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-08-28T04:03:33.270907"}